Expert Hardware / RTL Engineer – SystemVerilog / Verilog

About the Opportunity

A leading AI research organization is evaluating how advanced AI systems perform in specialized engineering domains, and is seeking expert hardware engineers with deep, hands-on RTL experience in SystemVerilog and/or Verilog. You'll apply your expertise to assess complex, real-world technical scenarios — directly shaping how cutting-edge AI performs in hardware design. Single-language specialists are strongly encouraged to apply.

What You'll Do

• Apply your RTL expertise to evaluate technical tasks against real-world professional standards
• Review intricate code-level situations and provide precise, structured written assessments
• Work inside containerized repositories (Docker), running and interpreting programmatic and CI-style checks to judge whether an engineering environment is sound
• Provide clear written rationales explaining your expert judgments
• Complete well-defined, time-bounded tasks with explicit evaluation criteria

Who We're Looking For

• We value strong engineering fundamentals, fast ramp-up, and high ownership over single-language pedigree alone — but deep specialists are very welcome. The ideal candidate brings:
• 5+ years of professional or research RTL experience in SystemVerilog or Verilog
• Hands-on depth in RTL design, testbench/UVM verification, FPGA or ASIC work, and EDA toolchains (Vivado, Quartus, Synopsys, Cadence)
• Comfort working in Linux/Docker-based repo environments and reading automated/CI checks — or the ability to ramp on these fast
• Ability to articulate not just what code does but why it's correct or idiomatic, clearly in writing
• Welcomed: engineers from semiconductor, telecom, defense/aerospace, national-lab, or academic backgrounds; non-traditional digital footprints are fine — a GitHub profile is not required

Why This Work Matters

RTL design underpins the world's semiconductors yet remains among the least-represented domains in AI research. The expertise you bring is rare, and your assessments directly influence how AI systems learn to operate in it.

Engagement Details

• Compensation: $110–190/hour, based on depth and experience
• Expected commitment: 20–40 hrs/week
• Task flow is variable — work tends to arrive in waves, and there can be a lag between task batches. We're looking for people who stay flexible, including availability on weekends when needed, and who take ownership of keeping the project moving forward
• No proprietary tooling required — tasks are completable without employer-provided systems
• We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.